Cigarette Smoking, Nicotine, and Body Weight

Audrain-McGovern, Janet; Nl, Benowitz

doi:10.1038/clpt.2011.105

Cited by 437 publications

(384 citation statements)

References 42 publications

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“…Men were found to use mainly smoking tobacco whilst women were consuming predominantly chewing tobacco [31–34]. These associations are in line with the literature for studies in many countries, which demonstrate that smokers have up to a 5 kg lower weight than non-smokers [35,36]. In this study, the difference in BMI between smokers and non-smokers was about 2 kg/m 2 corresponding to approximatively a 6 kg difference in weight for a man with a height of 1.7 m. This can be physiologically explained by the fact that nicotine increases thermogenesis in adipose tissue, partly by increasing lipolysis and subsequent recycling of fatty acids into triglycerides [37].…”

Section: Discussionsupporting

confidence: 68%

Gender differences in sociodemographic and behavioural factors associated with BMI in an adult population in rural Burkina Faso – an AWI-Gen sub-study

Boua

Sorgho

Rouamba

et al. 2018

Global Health Action

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Background: The global health transition is linked with an increased burden of non-communicable diseases with cardiovascular diseases leading the epidemic. In sub-Saharan Africa (SSA), the prevalence of obesity has increased during the past decades and there is a need to investigate the associated driving factors. In Burkina Faso obesity remains low, especially in rural areas. In this study we recruited middle-aged adults, as part of a larger study on genetic and environmental contributions to cardiometabolic disease among Africans. Objectives: To investigate the distribution of BMI and prevalence of obesity in a cross-sectional population-based study and to determine the sociodemographic and behavioural correlates with BMI. Methods: Participants (N = 2,076) were recruited from the Nanoro Health and Demographic Surveillance System area and were aged 40–60 years. We applied hierarchical modelling to identify factors associated with BMI and structural equation modelling to identify mediated effects of sociodemographic and behavioural variables on BMI. Results: Data are presented on 2,076 participants (49.9% female). Men had significantly higher BMI than women with medians of 21.1 (19.2 – 23.4) vs 19.8 (18.1 – 21.6) (p < 0.001), and there were significantly more underweight women compared to men (31.0% vs 17.4%) (p < 0.001). More men were overweight and obese than women (11.9% vs 5.2% and 2.2% vs 1.4%). Socioeconomic status was the major contributor to increased BMI for men, and education was the main contributor in women. Tobacco smoking and chewing, and problematic alcohol consumption were associated with a decrease in BMI in men and women. Conclusion: Overweight and obesity are relatively low among adults in rural Burkina Faso, and men had a higher median BMI than women. Behavioural factors, including tobacco use and alcohol consumption, contributed to a decrease in BMI, whereas socioeconomic status and education (which were both generally low in this community) contributed to an increase in BMI.

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Section: Discussionsupporting

confidence: 68%

Gender differences in sociodemographic and behavioural factors associated with BMI in an adult population in rural Burkina Faso – an AWI-Gen sub-study

Boua

Sorgho

Rouamba

et al. 2018

Global Health Action

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“…The lower risk effect of smoking could be due to subject's self-awareness to consume fewer cigarettes when presenting multiple risk factors or subjects being less capable of economically sustaining the habit while having to invest on medication to treat other health conditions. A review on the relationship between obesity and smoking 28 indicates that an inverse relationship between these two factors has been established by epidemiological studies, 29 as in the general population, smokers usually weigh less than non-smokers. 30 However, obese smokers tend to consume more cigarettes due to the reinforcement effect of nicotine and are at higher risk given the simultaneous presence of other lifestyle risk factors, including low fruit and vegetable intake, less physical activity and higher alcohol consumption.…”

Section: Discussionmentioning

confidence: 99%

Prevalence and risk factors associated with peripheral arterial disease in an adult population from Colombia

Urbano¹,

Portilla²,

Muñoz³

et al. 2018

Archivos de Cardiología de México

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Background: Cardiovascular diseases (CVD) are the most important cause of mortality in Latin America, while peripheral arterial disease (PAD) is the third leading cause of atherosclerotic cardiovascular morbidity. Objective: To establish the prevalence of PA D and the distribution of traditional CVD risk factors in a population from the Department of Cauca, Colombia. Methods: A cross-sectional study was conducted on a total of 10,000 subjects aged ≥40 years, from 36 municipalities. An ankle---brachial index (ABI) ≤ 0.9 in either leg was used as diagnostic criterion of PAD. Results: Overall PA D prevalence was 4.4% (4.7% females vs. 4.0% males), with diabetes being the most prevalent risk factor (23%). Among individuals self-reporting a history of acute myocardial infarction or stroke, PA D prevalence was 31.0% and 8.1%, respectively. After adjusting for potential confounders, PA D was significantly associated with hypertension (OR 4.6; 95% CI; 3.42---6.20), diabetes (4.3; 3.17---5.75), dyslipidaemia (3.1; 2.50---3.88), obesity (1.8; 1.37---2.30), and cigarette smoking (1.6; 1.26---1.94). Analysis for the interaction of risk factors showed that diabetes, dyslipidaemia, and obesity accounted for 13.2 times the risk for PA D (6.9---25.4), and when adding hypertension to the model, the risk effect was the highest (17.2; 8.4---35.1). Conclusions: Hypertension, diabetes, dyslipidaemia, and obesity, but not smoking were strong predictors of PAD. ABI measurement should be routinely performed as a screening test in

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“…This often explains why some smokers donʼt try to quit, especially women [26]. The average body weight of smokers is 4-5 kg less than that of non-smokers [27]. In other studies, the average BMI of smokers was shown to be at least 1 kg/m 2 lower than that of non-smokers [28,29].…”

Section: Discussionmentioning

confidence: 95%

“…The pathophysiology of the effect of cigarette smoking on body weight is not completely understood, although it is known that the main effects of smoking on body weight are mediated by nicotine. Nicotine is a sympathomimetic agent that increases energy expenditure by approximately 10% and promotes the release of several hormones which suppress appetite and increase satiety [27,30,31].…”

Section: Discussionmentioning

confidence: 99%

The Effects of Smoking on the Relationship Between Metabolic Syndrome and Arterial Stiffness

Kim

Wilson

Choi

et al. 2012

J UOEH

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: It has been reported that arterial stiffness assessed by pulse wave velocity (PWV) can predict cardiovascular morbidity and mortality. Metabolic syndrome and smoking are independently associated with increased risk of cardiovascular disease. The purpose of this study was to evaluate the effect of smoking on the relationship between metabolic syndrome and arterial stiffness. We retrospectively enrolled 1,530 men on whom brachial-ankle pulse wave velocity (baPWV) measurement had previously been performed as part of health screening at Kosin University Hospital. We found that PWV was positively correlated with the following variables: age (r = 0.391, P < 0.0001), systolic blood pressure (r = 0.438, P < 0.0001), diastolic blood pressure (r = 0.377, P < 0.0001), low-density lipoprotein (LDL) (r = 0.068, P = 0.008) and high-density lipoprotein (HDL) (r = 0.027, P = 0.287), whereas BMI was negatively correlated, although without statistical significance (r = -0.026, P = 0.309). Among current smokers, PWV decreased with increasing BMI (from 1,387.9 to 1,311.6), and increased with increasing HDL (from 1,342.7 to 1,385.4). On the other hand, among never smokers, PWV increased with increasing BMI (from 1,382.3 to 1,458.8), and decreased with increasing HDL (from 1,391.2 to 1,369.7). PWV was inversely associated with BMI and HDL, and these differences are likely due to smoking.

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Cigarette Smoking, Nicotine, and Body Weight

Cited by 437 publications

References 42 publications

Gender differences in sociodemographic and behavioural factors associated with BMI in an adult population in rural Burkina Faso – an AWI-Gen sub-study

Gender differences in sociodemographic and behavioural factors associated with BMI in an adult population in rural Burkina Faso – an AWI-Gen sub-study

Prevalence and risk factors associated with peripheral arterial disease in an adult population from Colombia

The Effects of Smoking on the Relationship Between Metabolic Syndrome and Arterial Stiffness

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